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Year 2026 · Volume 3 · Issue 2

Original Article

Artificial Neural Network Based Transient Stability Assessment of the Benin Sub Regional 330kv Network

Esene Christopher Akhimien1 M.J.E. Evbogbai2 H.E. Amhenrior3
1 2 3 Department of Electrical and Electronic Engineering, Edo State University, Iyamho, Edo State, Nigeria.

Published Online: May-August 2026

Pages: 33-37

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Abstract

This study investigates the application of Artificial Neural Networks (ANNs) for rapid and accurate prediction of Critical Clearing Time (CCT) in the Nigerian 330 kV Benin sub-regional transmission network. System data were obtained from the Transmission Company of Nigeria (TCN) and modeled using MATLAB/PSAT. The Extended Equal Area Criterion (EEAC) method was employed to compute target CCTs, while generation and load parameters were varied by ±10 % to produce diverse training scenarios. A feed-forward ANN was trained and validated using the Levenberg–Marquardt algorithm. The results demonstrated high predictive accuracy with R2 =0.999, mean squared error (MSE) = 0.0021, and mean absolute error (MAE) = 0.037 s. The ANN reduced computational time by over 90 % compared to traditional time-domain simulations. Graphical analyses confirmed that the ANN accurately predicts CCT values under different disturbance conditions, indicating its suitability for real-time transient stability assessment in large-scale grids

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References

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Citations

Esene Christopher Akhimien, M.J.E. Evbogbai, H.E. Amhenrior, “Artificial Neural Network Based Transient Stability Assessment of the Benin Sub Regional 330kv Network”, Indian Journal of Electrical and Electronics Engineering, Volume 03, Issue 02, May-August 2026, PP: 33-37.

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Licensing

© 2026 The Author(s). Published by Fifth Dimension Research Publication.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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